nep-rmg New Economics Papers
on Risk Management
Issue of 2008‒05‒24
three papers chosen by
Stan Miles
Thompson Rivers University

  1. Crisis and Hedge Fund Risk By Loriana Pelizzon; Monica Billio; Mila Getmansky
  2. Bank runs, liquidity and credit risk By Topi, Jukka
  3. Non-Parametric Analysis of Hedge Fund Returns: New Insights from High Frequency Data By Loriana Pelizzon; Monica Billio; Mila Getmansky

  1. By: Loriana Pelizzon (Department of Economics, University Of Venice Cà Foscari); Monica Billio (Department of Economics, University Of Venice Cà Foscari); Mila Getmansky (Department of Finance and Operations Management Isenberg School of Management University of Massachusetts)
    Abstract: We study the effect of financial crises on hedge fund risk. Using a regime-switching beta model, we separate systematic and idiosyncratic components of hedge fund exposure. The systematic exposure to various risk factors is conditional on market volatility conditions. We find that in the high-volatility regime (when the market is rolling-down and is likely to be in a crisis state) most strategies are negatively and significantly exposed to the Large-Small and Credit Spread risk factors. This suggests that liquidity risk and credit risk are potentially common factors for different hedge fund strategies in the down-state of the market, when volatility is high and returns are very low. We further explore the possibility that all hedge fund strategies exhibit a high volatility regime of the idiosyncratic risk, which could be attributed to contagion among hedge fund strategies. In our sample this event happened only during the Long-Term Capital Management (LTCM) crisis of 1998. Other crises including the recent subprime mortgage crisis affected hedge funds only through systematic risk factors, and did not cause contagion among hedge funds.
    Keywords: Hedge Fund, Risk Management, High frequency data
    JEL: G12 G29 C51
    Date: 2008
    URL: http://d.repec.org/n?u=RePEc:ven:wpaper:2008_10&r=rmg
  2. By: Topi, Jukka (Bank of Finland Research)
    Abstract: In this paper, I develop a model that addresses the links between banks’ liquidity outlook and their incentives to take credit risk. Assuming that both bank-specific liquidity shocks and credit losses are necessary to provoke bank runs, the model predicts that a bank’s incentives to mitigate its credit risk by screening decrease if the probability of a bank-specific liquidity shock declines. This suggests that the benign liquidity outlook prevailing prior to the subprime crisis may have contributed to the lack of screening by banks that has been an important causal factor in the crisis.
    Keywords: liquidity; credit risk screening; bank runs
    JEL: G12 G21 G28
    Date: 2008–05–14
    URL: http://d.repec.org/n?u=RePEc:hhs:bofrdp:2008_012&r=rmg
  3. By: Loriana Pelizzon (Department of Economics, University Of Venice Cà Foscari); Monica Billio (Department of Economics, University Of Venice Cà Foscari); Mila Getmansky (Department of Finance and Operations Management Isenberg School of Management University of Massachusetts)
    Abstract: This paper examines four different daily datasets of hedge fund return indexes: MSCI, FTSE, Dow Jones and HFRX, all based on investable hedge funds, and three different monthly datasets of hedge fund return indexes: CSFB, CISDM and HFR which comprise both investable and non-investable hedge funds. Our study, based on standard statistical analysis, non-parametric analysis of the distribution and non-parametric regressions with respect to the S&P500 index shows that key data biases and disparate index construction methodologies lead to different statistical properties of hedge fund databases. One key variable that highly affects the statistical properties of hedge fund index returns is the “investability” of hedge funds
    Keywords: Hedge Fund, Risk Management, High frequency data
    JEL: G12 G29 C51
    Date: 2008
    URL: http://d.repec.org/n?u=RePEc:ven:wpaper:2008_11&r=rmg

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